Visit-to-Visit Low-Density Lipoprotein Cholesterol Variability Is an Independent Determinant of Carotid Intima-Media Thickness in Patients With Type 2 Diabetes
Bibliographic record
Abstract
Background: Studies demonstrated that visit-to-visit variability in low-density lipoprotein cholesterol (LDLC) is an independent predictor of cardiovascular events in subjects with coronary artery disease. Whether visit-to-visit variability in LDLC levels affects subclinical atherosclerosis is unknown. This study sought to evaluate the role of visit-to-visit variability in LDLC levels on subclinical atherosclerosis. Methods: We evaluated 162 type 2 diabetic patients with measurement of carotid intima-media thickness (IMT). Intrapersonal mean and standard deviation (SD) of six measurements of LDLC during 12 months were calculated. Multivariate linear regressions assessed the independent correlates of carotid IMT. Results: The mean and SD of LDLC were 112 ± 22 and 15 ± 10 mg/dL, respectively, and 43.2% of patients were on hypolipidemic drugs. Age (standardized beta = 0.355, P < 0.001), male sex (standardized beta = 0.234, P = 0.002) and SD-LDLC (standardized beta = 0.201, P = 0.009) emerged as independent determinants of carotid maximum IMT independently of mean LDLC levels, body mass index (BMI), waist circumference, duration and treatment of diabetes, means and SDs of glycemic and other lipid variables, and uses of hypolipidemic and anti-hypertensive medications (R 2 = 0.15). Results did not change when mean IMT was used instead of maximum IMT. After controlling for age and sex, maximum IMT was thicker in patients with the highest compared to those with other three quartiles of SD-LDLC combined (1.14 ± 0.04 (SE) vs. 1.01 ± 0.02 mm, P = 0.01). Independent determinants of SD-LDLC were mean LDLC, use of hypolipidemic drugs, fasting triglyceride and visit-to-visit variability in HbA1c. Conclusions: Consistency of LDLC levels may be important to subclinical atherosclerosis in real-world patients with type 2 diabetes. It may be important for patients on lipid-lowering drugs to prevent non-compliance. J Clin Med Res. 2017;9(4):310-316 doi: https://doi.org/10.14740/jocmr2871w
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".